Predicting undernutrition among elementary schoolchildren in the Philippines using machine learning algorithms

Objectives This study aimed to compare the accuracy of four machine-learning (ML) algorithms, using two classification schemes, to predict undernutrition based on individual and household risk factors. Methods Data on public-school children were collected from a rural province (310 children) and a...

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Bibliographic Details
Main Authors: Siy Van, Vanessa T, Antonio, Victor A, Siguin, Carmina P, Gordoncillo, Normahitta P., Sescon, Joselito T., Go, Clark C, Miro, Eden Delight
Format: text
Published: Archīum Ateneo 2022
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Online Access:https://archium.ateneo.edu/mathematics-faculty-pubs/213
https://doi.org/10.1016/j.nut.2021.111571
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Institution: Ateneo De Manila University